Undergraduate Summer Research Internship:

1. Privacy-Preserving Machine Learning

2. Secure Crowdsourcing / Decentralized Apps

3. Secure Multi-party Computation

Secure Multi-party Computation (SMC) is getting more practical (e.g., 
https://sharemind.cyber.ee/research). There are numerous applications such 
as anonymous messaging
(https://www.usenix.org/conference/usenixsecurity17/technical-sessions/presentation/alexopoulos), 
privacy-preserving machine learning 
(https://eprint.iacr.org/2017/396.pdf), etc. This project will study 1 of 
these applications in details and use the latest open-source library to 
implement a prototype, e.g., ABY framework 
(https://github.com/encryptogroup/ABY).

4. Processing Encrypted Data

Homomorphic encryption allows computation over encrypted data without 
decryption. There are numerous applications such as biometric 
authentication (https://eprint.iacr.org/2016/484), genomic analysis 
(https://eprint.iacr.org/2017/294), machine learning 
(https://eprint.iacr.org/2017/396), etc. This project will study 1 of 
these applications in details and use the latest open-source library to 
implement a prototype, e.g., HElib (https://github.com/shaih/HElib).

5. SGX-enabled Application

Hardware enclaves (e.g., Intel SGX, AMD memory encryption) provides a 
hardware-enforced secure execution environment which can access encrypted 
enclave memory. This stimulates not only theoretical (e.g., 
https://eprint.iacr.org/2016/1071) but also practical (e.g., 
https://www.usenix.org/conference/nsdi17/technical-sessions/presentation/zheng) 
research. This project studies what else is now made possible/practical 
with this new technology. The focus can range from theoretical (with a 
formal security definition and the corresponding analysis) to practical 
(implement a prototype).

6. Cryptocurrency and Blockchain

New research keeps emerging every day. The project ranges from theoretical 
research to practical implementation. We can possibly study:

- OmniLedger: the first distributed ledger architecture that provides 
"scale-out" transaction processing capacity competitive with centralized 
payment processing systems such as Visa, without compromising security or 
support for permissionless decentralization (https://ia.cr/2017/406).

- Bulletproofs are designed to enable efficient confidential transactions 
in Bitcoin and other cryptocurrencies. Confidential transactions hide the 
amount that is transferred in the transaction 
(https://crypto.stanford.edu/bulletproofs).

7. Verifiable computation 

Verifiable computation enables efficient verification of result 
authenticity even if the computation is outsourced. It found applications 
in database query (e.g., 
http://legacydirs.umiacs.umd.edu/~zhangyp/papers/accum.pdf, 
https://www.ieee-security.org/TC/SP2017/papers/581.pdf), cloud computing, 
blockchain/smart contract, etc. The focus of the project can be 
theoretical or practical (e.g., https://github.com/scipr-lab/libsnark)

8. Security/Privacy/Cryptography/Blockchain/Machine Learning/Information 
Retrieval Project

I am interested in the these areas in general beyond those specific ideas.
I am also open to self-proposed projects.